Intelligent and Biosensors 2012 Part 8 pot

Intelligent and Biosensors 166 The total free energy in the FL is described by equation (3) based on the “Stoner- Wolfarth model” (Stoner & Wolfarth, 1948). θθθψθθ cossin)cos(sin)( 2 1 sin 22 sbstssxzu MHMHHMMNNKE −−−−−+= (3) Where H is the stray field generated by the magnetic nanoparticles, which can be divided into x H and y H , respectively. The demagnetizing factors can be determined by equation (4) (William, 2001). 22 /8 wlltwN z += , 22 /8 wlwtwN z += (4) According to the “Stoner- Wolfarth model”, the magnetization direction of the FL (FL is in a single domain state as the sensor size is in submicron range in this model) is determined by the minimization of the total free energy as shown in equation (3). Hence, the total free energy with respect to θ (Fig. 1-(c)) is minimized. Our method is to set up a discrete array of θ . The range of this array is from 0 to 2π and the step size is 0.00001. With such small step size, the range of θ can be considered as a continuous range. By substituting the array into equation (3), the minimized energy and the corresponding θ can be obtained using a simple algorithm. The next step is to use the following equation (5) to calculate the magnetoresistance (MR) ratio based on the magnetization (spin) configuration of GMR biosensor where the magnetization direction of PL is exchange biased to a fixed direction (-y). 2 )cos(1 0 Pf R R R R θθ −− ⎟ ⎠ ⎞ ⎜ ⎝ ⎛ Δ = Δ (5) Where f θ and p θ are the angles of the FL, and the PL with respect to EA, respectively; 0 )/( RRΔ is the MR ratio of the GMR biosensor when the FL and PL is antiparallel with each other, which is also the maximum MR ratio for a GMR biosensor. To evaluate the sensing performance, the relative MR change, δR, is needed to be defined by equation (6). (%)100sinsin 2 1 (%)100 )/( )/()/( ,, 0 ×−=× Δ Δ−Δ = withfwithoutf withwithout RR RRRR R θδ (6) Where with RR )/(Δ indicates the MR ratio of GMR biosensors due to the nanoparticle sensor agents immobilized on the surface of FL, without RR )/( Δ indicates the MR ratio without nanoparticle, especially SPNSA, on the surface of FL. Moreover, in equation (6), the θ f,without is the angle between FL magnetization and EA when no sensor agent is on the sensor surface and the θ f,with is the angle between FL magnetization and EA when the sensor agent is on the sensor surface. For FNSA, the θ f,without is zero, thus δR can be written by withf R , sin5.0 θ δ = . For SPNSA, the θ f,without is not zero due to the excitation field (see Fig. 1- (b)) and thus the δR can be rewritten by θ θ d f ⋅ cos5.0 , where, θ d is the angle difference before and after the SPNSA captured on the sensor surface (dθ = θ f,without - θ f,with ). The fringe field from the FL of GMR biosensors is also considered to affect the magnetic properties of nanoparticle sensor agent in both magnetization direction and magnetic moment due to the magnetic dipole interaction between the FL and the nanoparticles (see Fig. 1-(b)). In-Vitro Magnetoresistive Biosensors for Single Molecular Based Disease Diagnostics: Optimization of Sensor Geometry and Structure 167 Accordingly, the effect of fringe field from the FL on the δR is included in this model to precisely interpret the sensing performance. To find out how many percentages the FL fringe field would influence on the magnetic moment of the magnetic nanoparticles, the interaction factor (IF) defined as (%)100)/cos1( ' ⋅−= mm βα is employed, where ' m is the magnetic moment considering the effect of the FL fringe field, m is the original magnetic moment and β is the angle difference between the original magnetization of sensor agent and the rotated magnetization due to the fringe field from FL as shown in Fig. 1-(c). In this model, the FNSA is considered as a CoFe 2 O 4 nanoparticle. It has a remnant magnetization of 22 emu/g and a diameter of 26 nm (see Fig. 2-(a) and (b)). The magnetic moment of the CoFe 2 O 4 nanoparticle is calculated using VMm r π 4 ˆ = , where r M is the remnant magnetization and V is the volume of the CoFe 2 O 4 nanoparticle. Since the CoFe 2 O 4 nanoparticle has a large remnant magnetization, the excitation field ( t H ) is not required, thus the equation (3) can be simplified by equation (7), ffbffyffxffxzfu MHMHMHMNNKE θθθθθ cossincossin)( 2 1 sin 22 −−−−+= (7) Due to the fringe field from the FL of GMR biosensor ( H Δ ), the induced magnetic moment of the CoFe 2 O 4 nanoparticle becomes Hm f Δ ⋅ = Δ χ , where f χ is considered as constant because the fringe field is relatively small. In addition, by considering the single domain state of CoFe 2 O 4 nanoparticle agent, the magnetization direction of the CoFe 2 O 4 nanoparticle can be calculated using the “Stoner- Wolfarth model” as below: 33 '''2' )2/2/( sin , )2/2/( cos cossincossin)( 2 1 Dth lwtM H Dth lwtM H mHmHmHmHHE ff y ff x byxdu ++ =Δ ++ =Δ −Δ−Δ−+= θθ ββββ (8) where mmm Δ+= ' , and x H Δ , and y H Δ are the longitudinal, and transverse component of the FL fringe field, respectively. As the saturation magnetization of the CoFe 2 O 4 nanoparticle sensor agent is almost the same as the bulk CoFe 2 O 4 ferrite, the anisotropy constant, K 1 , of the sensor agent is assumed as bulk value of CoFe 2 O 4 ferrite, which is a 2×10 6 erg/cm 3 and thus ' 1 /2 mKH u = . The demagnetizing factor is considered as 3/4 π thus, 3/4 ' π ⋅= mH d . The SPN used in this model is also a single CoFe 2 O 4 nanoparticle but the diameter is a 7 nm as shown in Fig. 2-(c) and (d). As can be seen in the inset of Fig. 2-(c), the magnetic susceptibility, χ, of the superparamagnetic CoFe 2 O 4 nanoparticle is almost constant at a 0.041 independent of applied magnetic field. Using the experimentally obtained χ value, the magnetic moment of the superparamagnetic CoFe 2 O 4 nanoparticle under the b H and the t H is determined at 3/43/4 ˆ 33 zHrxHrm tb χπχπ += and the total free energy can be correspondingly re-written by equation (9). fft ffbffyffxffxzfu MH MHMHMHMNNKE θ θθθθθ sin cossincossin)( 2 1 sin 22 − −−−−+= (9) Intelligent and Biosensors 168 As the χ value is constant and there is no magnetic anisotropy energy under no excitation field, the IF for the superparamagnetic CoFe 2 O 4 nanoparticle sensor agent can be simplified as tyy HH /Δ= α , where y H Δ is the y component of the FL fringe field from GMR biosensor. (%)100 )2/2/( sin 3 × ++ = t fs HDth lwtM θ α (10) Fig. 2. (a) The hysteresis loop of CoFe 2 O 4 FNSA with a 26 nm particle size, and (b) the SEM (Scanning Electron Microscopy) image of the CoFe 2 O 4 FNSA, (c) the hysteresis loop of CoFe 2 O 4 SPNSA with a 7 nm particle size. The inset shows the minor hysteresis loop measured at a ± 300 Oe, and (d) the TEM (Transmission Electron Microscopy) image of the CoFe 2 O 4 SPNSA. 2.2 Comparison of sensing output performance Based on the physical model developed in section 2.1, the sensing output performance of an in-vitro GMR biosensor with a single immobilized FNSA or SPNSA is calculated and compared. Figure 3 shows the dependence of sensor width at the fixed sensor geometry (sensor aspect ratio) on the δR and the IF of the in-vitro GMR biosensors. The sensor width, W, of the GMR biosensor is changed from 10 to 80 nm at the different aspect ratio (L : W) changed from 3 : 1 to 10 : 1. The purpose of changing the sensor aspect ratio is to explore the effects of vortex magnetization on the surface of FL due to the geometrically-induced demagnetizing factor (Girgis et al., 2000). The H b , and the h are fixed at a 50 Oe, and a 30 nm, resepctively for precise comparison. The CoFe 2 O 4 FNSA, and SPNSA has a mean particle size of 26 nm and 7 nm, resepctively. The δR and its variation due to the change of W is numerically analyzed by considering both the “effective sensing area”, which is defined as the area formed on the FL surface whose magnetic spins can be coherently In-Vitro Magnetoresistive Biosensors for Single Molecular Based Disease Diagnostics: Optimization of Sensor Geometry and Structure 169 rotated by the stray magnetic field induced by the sensor agent, and the development of “inactive sensing area”, which is not responded by the stray field, due to the increase of IF induced by the geometrically-increased magnetic anisotropy of FL. Fig. 3. The physical dependence of sensor width, W, on the relative MR, δR, and the interaction factor, IF, (a) δR, GMR biosensor with a FNSA, (b) IF, GMR biosensor with a FNSA, (c) δR, GMR biosensor with a SPNSA, and (d) IF, GMR biosensor with a SPNSA. As shown in Fig. 3, the in-vitro GMR biosensors with an immobilized single FNSA or SPNSA exhibit the same physical characteristics that the δR is abruptly decreased above the maximized value obtained at the optimized sensor width, W op , and that the IF is almost squarely increased, by increasing the W as well as the aspect ratio. This is supposed to be due to the increase of “inactive sensing area” and the magnetic anisotropy of FL induced by the increased sensor size proportional to the W. However, it is clearly noted that the absolute δR and IF values of the in-vitro GMR biosensor with a FNSA are much larger than those with a SPNSA. As can be clearly seen in Fig. 3-(a) and (c), the δR obtained from the in- vitro GMR biosensor with an aspect ratio of 3: 1 (75 nm (L) × 25 nm (W op )) and an immobilized FNSA is a 2.72 %, while the δR for the in-vitro GMR biosensor with a SPNSA, which has the same aspect ratio (45 nm (L) × 15 nm (W op )), is a 0.013 %. In addition, the variation of IF values depending on the W of the in-vitro GMR biosensor with a FNSA is negligibly small compared to those with a SPNSA as shown in Fig. 3-(b) and (d). The practically allowable sensor size based on the physical limit of current sensor fabrication technology, especially nanoelectronics technology, is another physical parameter to be considered in evaluating the sensing performance. Considering the patterning limit of EBL Intelligent and Biosensors 170 (Electron Beam Lithography) technique (> 50 nm) and the geometrically-induced demagnetizing factor of FL directly relevant to the sensor aspect ratio and the IF, the minimum sensor size can be determined in the range between 150 nm (L) × 50 nm (W) and 250 (nm) × 50 nm (W). However, as verified in Fig. 3-(a) and (c), the δR values obtained from these sizes of in-vitro GMR biosensor with a SPNSA are too small to be considered for a real biosensor application. According to the numerically analyzed sensing performance summarized in Fig. 3, it is clearly demonstrated that an in-vitro GMR biosensor with an immobilized single CoFe 2 O 4 FNSA is more suitable for SMD due to its higher δR, less IF dependence, and practically allowable sensor size. The large remnant magnetization of single CoFe 2 O 4 FNSA allowing to produce a sufficiently large stray field and to maintain extremly small variation of IF is the main physical reason for the technical promise of GMR biosensor with an immobilized single FNSA for SMD. 3. Optimizing the sensor geometry of an in-vitro GMR biosensor with an immobilized FNSA for SMD In this chapter, the detailed spatial magnetic field interactions between the single CoFe 2 O 4 FNSA and the FL of an in-vitro GMR biosensor is numerically analyzed to predict the optimized sensor geometry that maximizes the sensng perfromance for SMD prior to fabrication. In order to more accurately analyze the spatial magentic field interactions on the FL surface, the longitudinal and the transverse components of the stray field produced by the FNSA are considered. The optimized sensor geometry at a given remnant magentic moment of the FNSA is predicted by evaluating the “effective sensing area”. The optimized sensor geometry is expressed in terms of the effective distance ( δ), which includes the radius, a, of FNSA, the length of biological entities (especially, DNA including probe), membrane thickness, and the passivation layer, as well as the critical sensor length (l c ), and the critical sensor width (w c ). The experimentally demonstrated sensing performance of an in-vitro GMR biosensor with an immobilized CoFe 2 O 4 FNSA is also compared to the numerically calculated sensing performance to confirm the effectiveness of the physical model introduced in this chapter. 3.1 Analytical model for optimizing sensor geometry and geometrical parameters Figure 4 shows the schematic diagram of an in-vitro GMR biosensor with an immobilized single FNSA (a) and the typical MR curve (b) obtained from the Si/Ta/Ni 80 Fe 20 /Ir 22 Mn 78 / Co 84 Fe 16 /Ru/Co 84 Fe 16 /Cu/Co 84 Fe 16 /Ni 80 Fe 20 /Ta exchange biased synthetic GMR spin- valve biosensor. For the numerical calculation, it is assumed that the CoFe 2 O 4 FNSA has an a = 250 nm, and a mass density of 5.29 g/cm 3 (Lee et al., 2007). By considering only the logitudinal field compoent of the stray field produced by the immobilized single CoFe 2 O 4 FNSA, B x on the surface of FL along the x and y axis from equation (2) is simplified by equation (11) (Schepper et al., 2006). 2/522 22 , 2/522 22 , )( )( 2 zy zy mB zx zx mB axisyx axisxx + −− ⋅= + − ⋅= − − (11) In-Vitro Magnetoresistive Biosensors for Single Molecular Based Disease Diagnostics: Optimization of Sensor Geometry and Structure 171 The calculated magnetic field distribution and the two geometrically critical parameters, which are essential to determine the optimized sensor geometry, are also denoted in Fig. 4- (a). The geometrical parameters of the in-vitro GMR biosensor with an immobilized single FNSA are first determined by considering the longitudinal component of the stray field. The effective magnetization, β , is defined as the ratio of the total magnetization of the CoFe 2 O 4 FNSA to the longitudinal field component of the stray field, x Bm /= β . The δ is defined as ah += δ . The geomtrical parameters, the l c , and the w c for achieving the optimized sensor geometry, which maximize the sensor output performance, are dependent on β and δ. These geometrical parameters, which determine the “effective sensing area”, cc wl × , are derived from equation (11) by considering x and y at the points where B x is equal to the sensor switching field, B sw (with xsw Bm / ≡ β ). The finally determined l c , and w c are given by, 23/2 3 3 22 54 222 δβ δβ δβ δ −== + − == swc sw sw c yw xl (12) The insert in Fig. 4-(b) highlights the two characteristic parameters relevant to the operation of the in-vitro GMR biosensor; the B sw and the detectable field limit (B DL ) directly associated with the exchange bias field of the in-vitro GMR biosensor, are defined in terms of the intensity of stray field produced by the single CoFe 2 O 4 FNSA. The critical effective distance, δ c , can be obtained by considering the operating conditions of the GMR biosensor including B sw , B DL , and the M r of the single CoFe 2 O 4 FNSA. If B x is in the sensor operating range, B sw <B x <B DL , δ can be expressed as a function of β. On the other hand, if B x is smaller than B sw (B sw >B x ), then 0== cc wl . Thus, the critical effective distance, δ c , for the sensor Fig. 4. (a) A schematic diagram of in-vitro GMR biosensor with an immobilized single FNSA, the field distribution , and the definition of geometrical parameters considering for optimizing sensor geometry, and (b) a typical MR curve of GMR biosensor and the definition of two sensing characteristics parameters. Intelligent and Biosensors 172 operation based on the non-switching conditions: B sw >B x , and equation (12) can be determined at 3 βδ = c . In addition, from equation (12), the aspect ratio, cc lw / for the optimized sensor geometry can be expressed by equation (13). )(2 )54()( 54 22 2 / 32 323/2 3 3 23/2 δβδ δβδβ δβ δβ δ δβ − +⋅− = + − ⋅ − = sw swsw sw sw sw cc lw (13) The numerically analyzed magnetic field distribution on the surface of the FL finally obtained by equation (13) clearly demonstrates that the optimized geometrical parameters, l c , and w c are directly relevant to δ and sw β . In order to more accurately predict the optimized sensor geometry based on the “effective sensing area, cc wl × ”, the numerical calculation is extended to two dimensional field component, both longitudinal and transverse field components, on the FL surface. The “Stoner- Wolfarth model” (or the “asteroid curve model”) is employed for the detailed calculation (Hirota et al., 2002). 3.2 Optimizing the sensor geometry considering the one dimensional (longitudinal) field component As described in the analytical model developed in section 3.1, the optimization of sensor geometry with an immobilized CoFe 2 O 4 FNSA is based on the determination of l c , and w c by considering the longitudinal field component of B x , and B y , on the FL surface. Figure 5 shows the contour diagrams of the magnetic field intensity and its distributions, B x , and B y on the FL surface as a function of δ (for δ = 0.5, 1.0, and 2.0 μm). As can be seen in Figs. 5-(a), 5-(c), and 5- (e), the maximum B x is rapidly decreased from 691.2 to 10.8 G by increasing δ from 0.5 to 2.0 μm. As shown in Fig. 4-(b), the in-vitro GMR biosensor considered in this model is operated at magnetic field intensity in the range from 12 G (B sw ) to 176 G (B DL ). Considering these the magnetic characteristics of GMR biosensor, the shaded region observed at δ = 0.5 μm due to the large field intensity (Fig. 5-(a)) and all the regions shown in Fig. 5-(e) do not contribute to the sensor operation. This indicates that the l c and the w c for the optimized sensor geometry based on equation (12) should be determined at δ c < 0.79 μm, which corresponds to the sensor operating condition of DLx BB ≤ . Furthermore, by combining the calculated value of δ c with the physical parameters of single CoFe 2 O 4 FNSA and equation (12), the l c , and the w c are determined to be ~ 1.12 μm, and ~ 3.52 μm. Based on the numerical calculation, the aspect ratio ( cc lw / ) for the optimized sensor geometry of in-vitro GMR biosensor with an immobilized single CoFe 2 O 4 FNSA (a = 250 nm) is determied at 14.3/ = cc lw . The calculation results shown in Fig. 5 clearly demonstrates that the geometrical and systematic design parameters ( δ, l c , and w c ) of the in-vitro GMR biosensor for producing a highly stable sensing performance can be precisely predicted prior to fabrication if the remnant magnetization of the single CoFe 2 O 4 FNSA and the GMR characteristics of the sensor are known. 3.3 Optimizing the sensor geometry considering the longitudinal and transverse field components Dependence of δ on the transverse component, B y , is also estimated to confirm its physical contribution to the optimization of in-vitro GMR biosensor geometry. Figure 5-(b), 5-(d), In-Vitro Magnetoresistive Biosensors for Single Molecular Based Disease Diagnostics: Optimization of Sensor Geometry and Structure 173 Fig. 5. Calculated contour diagrams of the longitudinal (left column) and transverse (right column) components of the magnetic field produced by an immobilized CoFe 2 O 4 FNSA on the FL surface where δ is varied from 0.5 to 2.0 μm. The area defined by the dashed-dotted line and the shaded region show the optimized sensor geometry, and the undetectable region, respectively. and 5-(f) show the contour diagrams of B y as a function of δ changed from 0.5 to 2.0 μm. Similar to the calculation results shown in Figs. 5-(a), 5-(c), and 5-(e), the B y has a strong dependence on δ. However, the distribution of B y is completely different from B x . The distribution of B x on the FL surface shows an ellipsoidal shape with the major axis along the y-axis, while B y exhibits a distribution that has a maximum and minimum field intensity of max,max, 3/1 xy BB ≈ at the position of (±δ, ∓ δ). The numerical comparison between B x and B y depending on δ suggests that both components of the stray field should be simultaneously Intelligent and Biosensors 174 considered for a more accurate prediction of the sensor geometry. Accordingly, the “Stoner- Wolfarth model”: 3/23/23/2 yxk HHH += , is employed to accurately analyze the spatial magnetic field distribution and intensity on the FL surface. Even though the “Stoner- Wolfarth model” assumes that the FL magnetizations are coherently rotated by the stray field and are homogneous across the entire FL surface, this model is considerably useful in interpreting the physical behavior of the in-vitro GMR biosensor under a highly localized magnetic dipole field from the immobilized single CoFe 2 O 4 FNSA. Figure 6 shows the magentic field distribution and intesity considering both the logitudinal and transverse field components with different effective distances: δ = 0.5, 1.0, and 2.0 μm. Unlike the ellipsoidal shape of the “effective sensing area” shown in Fig. 5, the coherently rotated magnetization of the FL induced by two-dimensional magnetic field components shows a more complicated and extended “effective sensing area” due to the contribution of the transverse field component. Figure 7 shows the optimized sensor geometry (white line) and the “effective sensing area” (bright gray region) calculated by considering the one-dimensional Fig. 6. The magnetic field distribution and intensity on the FL surface calculated by considering the longitudinal and transverse field components at the different effective distance of δ. (a) 0.5, (b) 1.0, and (c) 2.0 μm In-Vitro Magnetoresistive Biosensors for Single Molecular Based Disease Diagnostics: Optimization of Sensor Geometry and Structure 175 (Fig. 7-(a)) and the two-dimensional components (Fig. 7-(b)) based on the “Stoner- Wolfarth model”. Although the numerical values of optimized geometrical parameters determined at the effective distance of δ = 0.79 μm are the same as l c = 1.12 μm, and w c = 3.52 μm, the “effective sensing area” directly relevant to the sensing output performance is completely different. As can be seen in Fig. 7-(b), the “effective sensing area” is extended due to the transverse field component. This correspondingly results in enhancing the output signal of the in-vitro GMR biosensor. However, as can be also seen in Fig. 7-(b), an undetectable area in the vicinity of center of the optimized sensing area is developed due to the spatial magnetic field interaction. Making a GMR biosensor with a larger exchange bias field and introducing a specially designed sensor structure with a high permeability magnetic shield layer are suggested as an effective solution for the undesirable technical problem. Fig. 7. Comparison of the optimized sensor geometry (square region) and the “effective sensing area” calculated by considering the (a) one-dimensional filed component, and (b) two-dimensional field component on the FL surface. 3.4 Demonstration of sensing performance of the in-vitro GMR biosensors with optimized sensor geometry The sensing performance of an in-vitro GMR biosensor with an immobilized CoFe 2 O 4 ferrimagentic nanobead SA geomtrically optimized by the analytical model developed in chapter 3.1 is demontrated to confirm its practical effectiveness. The CoFe 2 O 4 nanobead with a mean raius, a, of 925 nm synthesized by using a modified sol-gel mehtod is considered as a ferrimagentic nanobead SA. The optimized sensor geomtry of the in-vitro GMR biosesnor based on the equations (11) ~ (13) as well as considering a 925 nm of mean nanobead size is calcuated to determine the “effective sensing area, cc wl × ”. The sensing output performance of the optimized GMR biosensors is evaluated as a function of sensor length, l, at the fixed w c by controlling the size of CoFe 2 O 4 nanobead SA, which is systematically varied in the range of a = 925 nm ± 20.5 % as shown in Fig. 8-(a). The controlled nanobead size leads to changing the l at the fixed w c due to the variation of stray field intensity caused by the change of effective distance. The GMR biosensor used for this demosntration has a strucutre of Si/Ta(5)/Ni 80 Fe 20 (2)/Ir 22 Mn 78 (20)/Co 84 Fe 16 (2)/ Ru(0.75)/Co 84 Fe 16 (2)/Cu(2.3)/Co 84 Fe 16 (0.5)/Ni 80 Fe 20 (2.5)/Ta(3 nm) and is patterned by using an electron beam lithography (EBL) and a typical photolithography. The patterned [...]... Geometry and Structure 183 integrated spin valve sensors: Biotechnological applications Journal of Applied Physics, Vol 91, No 10, pp 7 786 -7 788 , ISSN 0021 -89 79 Graham D L.; Ferreira H A.; Freitas P.P & Cabral J M S., (2003) High sensitivity detection of molecular recognition using magnetically labeled biomolecules and magnetoresistive sensors Biosensors and Bioelectronics, Vol 18, pp 483 - 488 , ISSN 0956-5663... mV.s-1 by applying a linear potential scan between – 400 mV and + 180 0 mV (vs Ag/AgCl) For some experimental runs the anodic difference 190 Intelligent and Biosensors square wave voltammogram (SWV) was collected in an oxidation direction only by applying a linear potential scan between – 400 mV and + 180 0 mV (vs Ag/AgCl), at a step potential of 4 mV, a frequency of 5 Hz, and a square amplitude of 50...176 Intelligent and Biosensors Fig 8 (a) Schematic diagram of in-vitro GMR biosensors with an immobilized CoFe2O4 ferrimagentic nanobead SA with different bead sizes controlled in the range of a = 925 nm ± 20.5 %, (2) the patterned GMR biosensor with the geomtry of l = 1 μm, and wc = 5 μm, and (c) GMR behaviour GMR biosensor structure and its GMR behaviour for the before and after patterning, and for... Mavrikou et al., 20 08; Liu et al., 20 08; Boon et al., 20 08; Pinheiro & De Andrade, 2009) A broad range of adverse effects can result from AChE inhibition and it includes abdominal pain and cramps, glandular secretions, skeletal muscle twitching, flaccid paralysis, tiredness, nausea, blurred vision, drowsiness, eye pain, convulsions, respiratory failure and untimely death Furthermore, OP and CM compounds... SA with a radius of 750 (-20.5 %, negative standard deviation), 925 (mean nano bead size), and 1150 nm (+20.5 %, positive standard deviation) is calculated by considering the experimentally obtained Mr values to determine the lc The calculated maximum field intensity is a 67 .8, 116.5, and 177.1 Oe (G), respectively and the lc is revealed to be a 0 .85 , 1. 08, and 1.31 μm, respectively at the fixed wc =... analysis of multiple samples (Liu et al., 20 08; Hildebrandt et al., 20 08) For this reason several rapid, relatively inexpensive, sensitive screening analytical techniques that need little sample pre-treatment are constantly being developed for the identification and quantification of OP and CM compounds (Liu et al., 20 08) Biosensors have filled the gap in this regard and these analytical devices are based... 310, pp 286 8- 287 0, ISSN 0304 -88 53 Li G & Wang S X., (2003) Analytical and micromagnetic modeling for detection og a single magnetic microbead or nanobead by spin valve sensors IEEE Transaction on Magnetics, Vol 39, No 5, pp 3313-3315, ISSN 10.1109 Megens M & Prins M., (2005) Magnetic biochips: a new option for sensitive diagnostics Journal of Magnetism and Magnetic Materials, Vol 293, pp 702-7 08, ISSN... magentic particle detection: Experimental verification of simulated behavior Journal of Applied Physics, Vol 99, No 103903, pp 1-4, ISSN 0021 -89 79 9 Mercaptobenzothiazole-on-Gold Organic Phase Biosensor Systems: 3 Thick-Film Biosensors for Organophosphate and Carbamate Pesticide Determination 1Natural V Somerset1, P Baker2 and E Iwuoha2 Resources and the Environment (NRE), Council for Scientific and Industrial... captured from the in-vitro GMR biosensor with geometry of l = 1 μm and w = 5 μm (a) activated by DC magnet, (b) activated by 750 nm size CoFe2O4 nanobead SA, (c) activated by 925 nm size CoFe2O4 nanobead SA, and (d) activated by 1150 nm size CoFe2O4 nanobead SA 1 78 Intelligent and Biosensors confirmed from the calcualtion results, the 0 .85 μm of lc determined by the 750 nm size of nanobead SA at the... to have mutagenic, carcinogenic and teratogenic effects and have been included in the list of known endocrine disruptor compounds (Luo & Zhang, 2009; Wu et al., 2009; Liu et al., 20 08; Fu et al., 2009; Caetano & Machado, 20 08) Due to the increasing toxicity and adverse effects of pesticides, many countries are now monitoring environmental and food samples for pesticides and have established maximum residue . Si/Ta(5)/Ni 80 Fe 20 (2)/Ir 22 Mn 78 (20)/Co 84 Fe 16 (2)/ Ru(0.75)/Co 84 Fe 16 (2)/Cu(2.3)/Co 84 Fe 16 (0.5)/Ni 80 Fe 20 (2.5)/Ta(3 nm) and is patterned by using an electron beam lithography (EBL) and. biomolecules and magnetoresistive sensors. Biosensors and Bioelectronics, Vol. 18, pp. 483 - 488 , ISSN 0956-5663 Graham D. L.; Ferreira H. A. & Freitas P.P., (2004). Magnetoresistive-based biosensors. ferrite nanoparticles for hypertheria application. Journal of Magnetism and Magnetic Materials, Vol. 310, pp. 286 8- 287 0, ISSN 0304 -88 53 Li G. & Wang S. X., (2003). Analytical and micromagnetic